Search results for: optimal chiller loading

Authors: Chaozhi Yang, Xinzhong Chen, Guoqing Huang

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Inerter is a two-terminal inertial element that can produce apparent mass far larger than its physical mass. A double tuned inertial mass damper (DTIMD) is developed by combining a spring with an inerter and a dashpot in series to replace the viscous damper of a tuned mass damper (TMD), and its performance is investigated. Firstly, the DTIMD is optimized numerically with H∞ and H2 methods considering the system’s damping based on the single-degree-of-freedom (SDOF)-DTIMD system, and the optimal structural parameters are obtained. Then, compared with a TMD, the control effect of the DTIMD with the optimal structural parameters on wind-induced vibration of a wind turbine in downwind direction under the shutdown condition is studied. The results demonstrate that the vibration suppression of the DTIMD is superior than that of a TMD at the same mass ratio. And at the identical vibration suppression, the tuned mass of the DTIMD can be reduced by up to 40% compared with a TMD.

Keywords: wind-induced vibration, vibration control, inerter, tuned mass damper, damped system

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Authors: P. R. Prabhu, S. M. Kulkarni, S. S. Sharma, K. Jagannath, Achutha Kini U.

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In the present study, response surface methodology has been used to optimize turn-assisted deep cold rolling process of AISI 4140 steel. A regression model is developed to predict surface hardness and surface roughness using response surface methodology and central composite design. In the development of predictive model, deep cold rolling force, ball diameter, initial roughness of the workpiece, and number of tool passes are considered as model variables. The rolling force and the ball diameter are the significant factors on the surface hardness and ball diameter and numbers of tool passes are found to be significant for surface roughness. The predicted surface hardness and surface roughness values and the subsequent verification experiments under the optimal operating conditions confirmed the validity of the predicted model. The absolute average error between the experimental and predicted values at the optimal combination of parameter settings for surface hardness and surface roughness is calculated as 0.16% and 1.58% respectively. Using the optimal processing parameters, the hardness is improved from 225 to 306 HV, which resulted in an increase in the near surface hardness by about 36% and the surface roughness is improved from 4.84µm to 0.252 µm, which resulted in decrease in the surface roughness by about 95%. The depth of compression is found to be more than 300µm from the microstructure analysis and this is in correlation with the results obtained from the microhardness measurements. Taylor Hobson Talysurf tester, micro Vickers hardness tester, optical microscopy and X-ray diffractometer are used to characterize the modified surface layer.

Keywords: hardness, response surface methodology, microstructure, central composite design, deep cold rolling, surface roughness

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Authors: A. Lambert-Mogiliansky

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In this paper, we investigate the properties of simple rules for reappointment aimed at holding a public official accountable and monitor his activity. The public official allocates budget resources to various activities which results in the delivery of public services to citizens. He has discretion over the use of resource so he can divert some of them for private ends. Because of a liability constraint, zero diversion can never be secured in all states. The optimal reappointment mechanism under complete information is shown to exhibit some leniency thus departing from the zero tolerance principle. Under asymmetric information (about the state), a rule with random verification in a pre-announced subset is shown to be optimal in a class of common rules. Surprisingly, those common rules make little use of hard information about service delivery when available. Similarly, PO's claim about his record is of no value to improve the performance of the examined rules. In contrast requesting that the PO defends his records publicly can be very useful if the service users are given the chance to refute false claims with cheap talk complaints: the first best complete information outcome can be approached in the absence of any observation by the manager of the accountability mechanism.

Keywords: accountability, corruption, persuasion, debate

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Authors: Nurul Na'imy Wan, Mohamad Sazali Said, Jaharah Ab. Ghani, Mohd Asri Selamat

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This paper presents the surface roughness of the Aluminium silicon alloy (AlSi) matrix composite which has been reinforced with aluminium nitride (AlN), with three types of carbide inserts. Experiments were conducted at various cutting speeds, feed rates, and depths of cut, according to the Taguchi method, using a standard orthogonal array L27 (34). The signal-to-noise (S/N) ratio and analysis of variance are applied to study the characteristic performance of machining parameters in measuring the surface roughness during the milling operation. The analysis of results, using the Taguchi method concluded that a combination of low feed rate, medium depth of cut, low cutting speed, and insert TiB2 give a better value of surface roughness. From Taguchi method, it was found that cutting speed of 230m/min, feed rate of 0.4 mm/tooth, depth of cut of 0.5mm and type of insert of TiB2 were the optimal machining parameters that gave the optimal value of surface roughness.

Keywords: AlSi/AlN Metal Matrix Composite (MMC), surface roughness, Taguchi method

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Authors: Mohammad H. Almomani

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In this paper, we argue the effect of the initial sample size, and the increment in simulation samples on the performance of a sequential approach that used in selecting the top m designs when the number of alternative designs is very large. The sequential approach consists of two stages. In the first stage the ordinal optimization is used to select a subset that overlaps with the set of actual best k% designs with high probability. Then in the second stage the optimal computing budget is used to select the top m designs from the selected subset. We apply the selection approach on a generic example under some parameter settings, with a different choice of initial sample size and the increment in simulation samples, to explore the impacts on the performance of this approach. The results show that the choice of initial sample size and the increment in simulation samples does affect the performance of a selection approach.

Keywords: Large Scale Problems, Optimal Computing Budget Allocation, ordinal optimization, simulation optimization

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Authors: Raouf Alizadeh, Kadijeh Hemmati

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The aim of this study is to synthesize several series of hydrogels from combination of a natural based polymer (Quince seed mucilage QSD), a synthetic copolymer contained methoxy poly ethylene glycol -polycaprolactone (mPEG-PCL) in the presence of different amount of multi-walled carbon nanotube (f-MWNT). Mono epoxide functionalized mPEG (mP EG-EP) was synthesized and reacted with sodium azide in the presence of NH4Cl to afford mPEG- N3(-OH). Then ring opening polymerization (ROP) of ε–caprolactone (CL) in the presence of mPEG- N3(-OH) as initiator and Sn(Oct)2 as catalyst led to preparation of mPEG-PCL- N3(-OH ) which was grafted onto propagylated f-MWNT by the click reaction to obtain mPEG-PCL- f-MWNT (-OH ). In the presence of mPEG- N3(-Br) and mixture of NHS/DCC/ QSD, hybrid hydrogels were successfully synthesized. The copolymers and hydrogels were characterized using different techniques such as, scanning electron microscope (SEM) and thermogravimetric analysis (TGA). The gel content of hydrogels showed dependence on the weight ratio of QSD:mPEG-PCL:f-MWNT. The swelling behavior of the prepared hydrogels was also studied under variation of pH, immersion time, and temperature. According to the results, the swelling behavior of the prepared hydrogels showed significant dependence in the gel content, pH, immersion time and temperature. The highest swelling was observed at room temperature, in 60 min and at pH 8. The loading and in-vitro release of quercetin as a model drug were investigated at pH of 2.2 and 7.4, and the results showed that release rate at pH 7.4 was faster than that at pH 2.2. The total loading and release showed dependence on the network structure of hydrogels and were in the range of 65- 91%. In addition, the cytotoxicity and release kinetics of the prepared hydrogels were also investigated.

Keywords: antioxidant, drug delivery, Quince Seed Mucilage(QSD), swelling behavior

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Authors: Mequanent Wale Mekonen, Edoardo Otranto, Angela Alibrandi

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Diabetic kidney disease is one of the main microvascular complications caused by diabetes. Several clinical and biochemical variables are reported to be associated with diabetic kidney disease in people with type 2 diabetes. However, their interrelations could distort the effect estimation of these variables for the disease's progression. The objective of the study is to determine how the biochemical and clinical variables in people with type 2 diabetes are interrelated with each other and their effects on kidney disease progression through advanced statistical methods. First, principal component analysis was used to explore how the biochemical and clinical variables intercorrelate with each other, which helped us reduce a set of correlated biochemical variables to a smaller number of uncorrelated variables. Then, ordered logit regression models (cumulative, stage, and adjacent) were employed to assess the effect of biochemical and clinical variables on the order-level response variable (progression of kidney function) by considering the proportionality assumption for more robust effect estimation. This retrospective cross-sectional study retrieved data from a type 2 diabetic cohort in a polyclinic hospital at the University of Messina, Italy. The principal component analysis yielded three uncorrelated components. These are principal component 1, with negative loading of glycosylated haemoglobin, glycemia, and creatinine; principal component 2, with negative loading of total cholesterol and low-density lipoprotein; and principal component 3, with negative loading of high-density lipoprotein and a positive load of triglycerides. The ordered logit models (cumulative, stage, and adjacent) showed that the first component (glycosylated haemoglobin, glycemia, and creatinine) had a significant effect on the progression of kidney disease. For instance, the cumulative odds model indicated that the first principal component (linear combination of glycosylated haemoglobin, glycemia, and creatinine) had a strong and significant effect on the progression of kidney disease, with an effect or odds ratio of 0.423 (P value = 0.000). However, this effect was inconsistent across levels of kidney disease because the first principal component did not meet the proportionality assumption. To address the proportionality problem and provide robust effect estimates, alternative ordered logit models, such as the partial cumulative odds model, the partial adjacent category model, and the partial continuation ratio model, were used. These models suggested that clinical variables such as age, sex, body mass index, medication (metformin), and biochemical variables such as glycosylated haemoglobin, glycemia, and creatinine have a significant effect on the progression of kidney disease.

Keywords: diabetic kidney disease, ordered logit model, principal component analysis, type 2 diabetes

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Authors: Ali Ravangard, S. Mohammadi

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Shunt Capacitors have several uses in the electric power systems. They are utilized as sources of reactive power by connecting them in line-to-neutral. Electric utilities have also connected capacitors in series with long lines in order to reduce its impedance. This is particularly common in the transmission level, where the lines have length in several hundreds of kilometers. However, this post will generally discuss shunt capacitors. In distribution systems, shunt capacitors are used to reduce power losses, to improve voltage profile, and to increase the maximum flow through cables and transformers. This paper presents a new method to determine the optimal locations and economical sizing of fixed and/or switched shunt capacitors with a view to power losses reduction and voltage stability enhancement. For solving the problem, a new enhanced cuckoo optimization algorithm is presented.The proposed method is tested on distribution test system and the results show that the algorithm suitable for practical implementation on real systems with any size.

Keywords: capacitor placement, power losses, voltage stability, radial distribution systems

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Authors: Şeyma Saliha Fidan, Rahmi Ünal

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Ceramic materials exhibit inherently brittle behavior, primarily attributed to the presence of flaws that severely restrict their applicability as structural elements under tensile loading. This brittleness necessitates special attention in the design of ceramic components, with a particular focus on appropriately addressing stress distribution. Among the most commonly used uniaxial testing methods to evaluate the mechanical behavior of ceramics are three-point bending and four-point bending tests. Each of these methods induces a unique stress distribution within the specimen. Using Weibull theory and its fundamental assumptions, it is possible to account for the different stress fields produced by each testing method and compare the resulting strength data. This comparison is based on the concept of effective volume or area. In this study, slip-cast fused silica ceramics were selected as the material of interest. The study aims to apply Weibull statistical theory to various testing methods, integrating statistical tools and finite element method (FEM) simulations. A validated FEM-based approach was developed to determine the effective volumes of the specimens. The effective volume values obtained through analytical and numerical methods were compared, and the stress fields generated by different testing methods were evaluated based on Weibull theory. Moreover, the effective volume calculation procedure derived from numerical analysis methods has been adapted for use in complex test geometries and various loading conditions.

Keywords: ceramic, fused silica, effective volume, Weibull analysis, finite element method

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Authors: N. Chayaopas, W. Assawinchaichote

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In order to maximize energy capturing from wind energy, controlling the doubly fed induction generator to have optimal power from the wind, generator speed and output electrical power control in wind energy system have a great importance due to the nonlinear behavior of wind velocities. In this paper purposes the design of a control scheme is developed for power control of wind energy system via H∞ fuzzy integral controller. Firstly, the nonlinear system is represented in term of a TS fuzzy control design via linear matrix inequality approach to find the optimal controller to have an H∞ performance are derived. The proposed control method extract the maximum energy from the wind and overcome the nonlinearity and disturbances problems of wind energy system which give good tracking performance and high efficiency power output of the DFIG.

Keywords: doubly fed induction generator, H-infinity fuzzy integral control, linear matrix inequality, wind energy system

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Authors: Ibrahim Watad, Ibrahim Abdulhalim

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Conventional spectroscopic surface plasmon resonance (SPR) sensors are widely used, both in fundamental research and environmental monitoring as well as healthcare diagnostics. However, they still lack the low limit of detection (LOD) and there still a place for improvement. SPR conventional sensors are based on the detection of a dip in the reflectivity spectrum which is relatively wide. To improve the performance of these sensors, many techniques and methods proposed either to reduce the width of the dip or to increase the sensitivity. Together with that, profiting from the sharp jump in the phase spectrum under SPR, several works suggested the extraction of the phase of the reflected wave. However, existing phase measurement setups are in general more complicated compared to the conventional setups, require more stability and are very sensitive to external vibrations and noises. In this study, a simple polarimetric technique for phase extraction under SPR is presented, followed by a theoretical error analysis and an experimental verification. The advantages of the proposed technique upon existing techniques will be elaborated, together with conclusions regarding the best polarimetric function, and its corresponding optimal metal layer range of thicknesses to use under the conventional Kretschmann-Raether configuration.

Keywords: plasmonics, polarimetry, thin films, optical sensors

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Authors: Mustafa Al-Refai

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This paper presents the optimal design and simulation of a grid-connected Photovoltaic (PV) system to supply electric power to meet the energy demand by Electrical Department in University of Tripoli Libya. Solar radiation is the key factor determining electricity produced by photovoltaic (PV) systems. This paper is designed to develop a novel method to calculate the solar photovoltaic generation capacity on the basis of Mean Global Solar Radiation data available for Tripoli Libya and finally develop a system design of possible plant capacity for the available roof area. MatLab/Simulink Programming tools and monthly average solar radiation data are used for this design and simulation. The specifications of equipments are provided based on the availability of the components in the market. Simulation results and analyses are presented to validate the proposed system configuration.

Keywords: photovoltaic (PV), grid, Simulink, solar energy, power plant, solar irradiation

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Authors: Lubem Matthew Kwaghkor

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Terrorism, which remains one of the largest threats faced by various nations and communities around the world, including Nigeria, is the calculated use of violence to create a general climate of fear in a population to attain particular goals that might be political, religious, or economical. Several terrorist groups are currently active in Nigeria, leading to attacks on both civil and military targets. Among these groups, Boko Haram is the deadliest terrorist group operating majorly in Borno State. The southern part of Borno State in North-Eastern Nigeria has been plagued by terrorism, insurgency, and conflict for several years. Understanding the dynamics of terrorism is crucial for developing effective strategies to mitigate its impact on communities and to facilitate peace-building efforts. This research aims to develop a mathematical model that captures the dynamics of terrorism within the southern part of Borno State, Nigeria, capturing both government and local community intervention strategies as control measures in combating terrorism. A compartmental model of five nonlinear differential equations is formulated. The model analyses show that a feasible solution set of the model exists and is bounded. Stability analyses show that both the terrorism free equilibrium and the terrorism endermic equilibrium are asymptotically stable, making the model to have biological meaning. Optimal control theory will be employed to identify the most effective strategy to prevent or minimize acts of terrorism. The research outcomes are expected to contribute towards enhancing security and stability in Southern Borno State while providing valuable insights for policymakers, security agencies, and researchers. This is an ongoing research.

Keywords: modelling, terrorism, optimal control, susceptible, non-susceptible, community intervention

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Authors: A. A. Okafor, C. H. Achebe, J. L. Chukwuneke, C. G. Ozoegwu

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The performance of an engine whose basic design parameters are known can be predicted with the assistance of simulation programs into the less time, cost and near value of actual. This paper presents a comprehensive mathematical model of the performance parameters of four stroke spark ignition engine. The essence of this research work is to develop a mathematical model for the analysis of engine performance parameters of four stroke spark ignition engine before embarking on full scale construction, this will ensure that only optimal parameters are in the design and development of an engine and also allow to check and develop the design of the engine and it’s operation alternatives in an inexpensive way and less time, instead of using experimental method which requires costly research test beds. To achieve this, equations were derived which describe the performance parameters (sfc, thermal efficiency, mep and A/F). The equations were used to simulate and optimize the engine performance of the model for various engine speeds. The optimal values obtained for the developed bivariate mathematical models are: sfc is 0.2833kg/kwh, efficiency is 28.77% and a/f is 20.75.

Keywords: bivariate models, engine performance, injector engine, optimization, performance parameters, simulation, spark ignition

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Authors: Uchenna Egwu, Paul Jonathan Sallis

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Perennial ryegrass is an abundant renewable lignocellulosic biofuel feedstock for biomethane production through anaerobic digestion (AD). In this study, six anaerobic continuously stirred tank reactors (CSTRs) were set up in three pairs. Each pair of the CSTRs was then used to study the effects of operating temperatures – psychrophilic, mesophilic, and thermophilic, and optimum pH on the specific methane production (SMP) of the ryegrass during AD under discontinuous daily feeding conditions. The reactors were fed at an organic loading rate (OLR) ranging from 1-1.5 kgVS.L⁻¹d⁻¹ and hydraulic residence time, HRT=20 days for 140 days. The pH of the digesters was maintained at the range of 6.8-7.2 using 1 M NH₄HCO₃ solution, but this was replaced with biomass ash-extracts from day 105-140. The results obtained showed that the mean SMP of ryegrass measured between HRT 3 and 4 were 318.4, 425.4 and 335 N L CH₄ kg⁻¹VS.d⁻¹ for the psychrophilic (25 ± 2°C), mesophilic (40 ± 1°C) and thermophilic (60 ± 1°C) temperatures respectively. It was also observed that the buffering ability of the reactors increased with operating temperature, probably due to an increase in the solubility of ammonium bicarbonate (NH₄HCO₃) with temperature. The reactors also achieved a mean VS destruction of 61.9, 68.5 and 63.5%, respectively, which signifies that the mesophilic reactors achieved the highest specific methane production (SMP), while the psychrophilic reactors achieved the lowest. None of the reactors attained steady-state condition due to the discontinuous daily feeding times, and therefore, such feeding practice may not be the most effective for maximum biogas production over long periods of time. The addition of NH₄HCO₃ as supplement provided a good buffering condition in these AD digesters, but the digesters failed in the long run due to inhibition from the accumulation of free ammonia, which later led to decrease in pH, acidification, and souring of the digesters. However, the addition of biomass ash extracts was shown to potentially revive failed AD reactors by providing an adequate buffering and essential trace nutrient supplements necessary for optimal bacterial growth.

Keywords: anaerobic digestion, discontinuous feeding, perennial ryegrass, specific methane production, supplements, temperature

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Authors: Asma Shaheen, Javed Iqbal

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The water resources are depleting due to an intrusion of industrial pollution. There are clusters of industries including leather tanning, textiles, batteries, and chemical causing contamination. These industries use bulk quantity of water and discharge it with toxic effluents. The penetration of heavy metals through irrigation from industrial effluent has toxic effect on soil and groundwater. There was strong positive significant correlation between all the heavy metals in three media of industrial effluent, soil and groundwater (P < 0.001). The metal to the metal association was supported by dendrograms using cluster analysis. The geospatial variability was assessed by using geographically weighted regression (GWR) and pollution model to identify the simulation of carcinogenic elements in soil and groundwater. The principal component analysis identified the metals source, 48.8% variation in factor 1 have significant loading for sodium (Na), calcium (Ca), magnesium (Mg), iron (Fe), chromium (Cr), nickel (Ni), lead (Pb) and zinc (Zn) of tannery effluent-based process. In soil and groundwater, the metals have significant loading in factor 1 representing more than half of the total variation with 51.3 % and 53.6 % respectively which showed that pollutants in soil and water were driven by industrial effluent. The cumulative eigen values for the three media were also found to be greater than 1 representing significant clustering of related heavy metals. The results showed that heavy metals from industrial processes are seeping up toxic trace metals in the soil and groundwater. The poisonous pollutants from heavy metals turned the fresh resources of groundwater into unusable water. The availability of fresh water for irrigation and domestic use is being alarming.

Keywords: groundwater, geostatistical, heavy metals, industrial effluent

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Authors: Ksenija Dumičić, Anita Čeh Časni, Berislav Žmuk

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The aim of this paper is to select the most accurate forecasting method for predicting the future values of the unemployment rate in selected European countries. In order to do so, several forecasting techniques adequate for forecasting time series with trend component, were selected, namely: double exponential smoothing (also known as Holt`s method) and Holt-Winters` method which accounts for trend and seasonality. The results of the empirical analysis showed that the optimal model for forecasting unemployment rate in Greece was Holt-Winters` additive method. In the case of Spain, according to MAPE, the optimal model was double exponential smoothing model. Furthermore, for Croatia and Italy the best forecasting model for unemployment rate was Holt-Winters` multiplicative model, whereas in the case of Portugal the best model to forecast unemployment rate was Double exponential smoothing model. Our findings are in line with European Commission unemployment rate estimates.

Keywords: European Union countries, exponential smoothing methods, forecast accuracy unemployment rate

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Authors: D. Kumar, S. Kumar, A. G. Memon, R. A. Memon, K. Harijan

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A considerable amount of energy is usually lost due to compression of insulation in Heating, ventilation, and air conditioning (HVAC) duct. In this paper, the economic impact of compression of insulation is estimated. Relevant mathematical models were used to estimate the optimal thickness at the points of compression. Furthermore, the payback period is calculated for the optimal thickness at the critical parts of supply air duct (SAD) and return air duct (RAD) considering natural gas (NG) and liquefied petroleum gas (LPG) as fuels for chillier operation. The mathematical model is developed using preliminary data obtained for an HVAC system of a pharmaceutical company. The higher heat gain and cooling loss, due to compression of thermal insulation, is estimated using relevant heat transfer equations. The results reveal that maximum energy savings (ES) in SAD is 34.5 and 40%, while in RAD is 22.9% and 29% for NG and LPG, respectively. Moreover, the minimum payback period (PP) for SAD is 2 and 1.6years, while in RAD is 4.3 and 2.7years for NG and LPG, respectively. The optimum insulation thickness (OIT) corresponding to maximum ES and minimum PP is estimated to be 35 and 42mm for SAD, while 30 and 38mm for RAD in case of NG and LPG, respectively.

Keywords: optimum insulation thickness, life cycle cost analysis, payback period, HVAC system

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Authors: Fanqiang Kong, Chending Bian

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Sparse unmixing is a promising approach in a semisupervised fashion by assuming that the observed pixels of a hyperspectral image can be expressed in the form of linear combination of only a few pure spectral signatures (end members) in an available spectral library. However, the sparse unmixing problem still remains a great challenge at finding the optimal subset of endmembers for the observed data from a large standard spectral library, without considering the spatial information. Under such circumstances, a sparse unmixing algorithm termed as non-local simultaneous sparse unmixing (NLSSU) is presented. In NLSSU, the non-local simultaneous sparse representation method for endmember selection of sparse unmixing, is used to finding the optimal subset of endmembers for the similar image patch set in the hyperspectral image. And then, the non-local means method, as a regularizer for abundance estimation of sparse unmixing, is used to exploit the abundance image non-local self-similarity. Experimental results on both simulated and real data demonstrate that NLSSU outperforms the other algorithms, with a better spectral unmixing accuracy.

Keywords: hyperspectral unmixing, simultaneous sparse representation, sparse regression, non-local means

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Authors: Mahdi Mottahedi, Peter Zahn, Armin Lechler, Alexander Verl

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Optimal topology of components leads to the maximum stiffness with the minimum material use. For the generation of these topologies, normally algorithms are employed, which tackle manufacturing limitations, at the cost of the optimal result. The global optimum result with penalty factor one, however, cannot be fabricated with conventional methods. In this article, an additive manufacturing method is introduced, in order to enable the production of global topology optimization results. For a benchmark, topology optimization with higher and lower penalty factors are performed. Different algorithms are employed in order to interpret the results of topology optimization with lower factors in many microstructure layers. These layers are then joined to form the final geometry. The algorithms’ benefits are then compared experimentally and numerically for the best interpretation. The findings demonstrate that by implementation of the selected algorithm, the stiffness of the components produced with this method is higher than what could have been produced by conventional techniques.

Keywords: topology optimization, additive manufacturing, 3D-printer, laminated object manufacturing

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Authors: Sanat Ramesh, Tarun Dutt, Abhilasha Aswal, Anushka Chandrababu, G. N. Srinivasa Prasanna

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Optimal Schedule Generation for a large national railway network operating thousands of passenger trains with tens of thousands of kilometers of track is a grand computational challenge in itself. We present heuristics based on a Mixed Integer Program (MIP) formulation for local optimization. These methods provide flexibility in scheduling new trains with varying speed and delays and improve utilization of infrastructure. We propose methods that provide a robust solution with hundreds of trains being scheduled over a portion of the railway network without significant increases in delay. We also provide techniques to validate the nominal schedules thus generated over global correlated variations in travel times thereby enabling us to detect conflicts arising due to delays. Our validation results which assume only the support of the arrival and departure time distributions takes an order of few minutes for a portion of the network and is computationally efficient to handle the entire network.

Keywords: mixed integer programming, optimization, railway network, train scheduling

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Authors: Pui-Lai To, Chechen Liao, Ming-Chi Sung

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Work and family life are the most important areas for men and women today. Every professional is required to meet and fulfill the responsibilities of work and family roles. Although the development and popularity of communication technology bring a lot of benefits, including effective and efficient communication, may also generate conflicts between work and family life. Since mobile devices and the applications of mobile devices, such as instant messages, are ubiquitous, the boundaries of work and family roles are increasingly blurred. Professionals may be in the risk of work over-loading and work-family conflict. This study examines the impact of work stress on professionals’ life and health in the context of instant messaging application of smart phone. This study uses a web-based questionnaire to collect samples. The questionnaires are sent via virtual community sites, instant messaging applications, and e-mail. The study develops and empirically validates a work-family conflict model by integrating the pressure theory and technostress factors. The causal relationship between variables in the research model is tested. In terms of data analysis, Partial Least Square (PLS) in Structural Equation Modeling (SEM) is used for sample analysis and research model testing. The results of this study are as follows. First, both the variables of work-related stress and technological violations positively affect the work-family conflict. Second, both the variables of work-loading and technology-overloading have no effect on work-family conflict. Third, work-family conflict has negative effect on job satisfaction, family satisfaction, physical health, and mental health.

Keywords: mental health, physical health, technostress, work-family conflict, work-related stress

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Authors: Ling Ai Wong, Hussain Shareef, Azah Mohamed, Ahmad Asrul Ibrahim

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The installation of photovoltaic based distributed generation (PVDG) in active distribution system can lead to voltage fluctuation due to the intermittent and unpredictable PVDG output power. This paper presented a method in mitigating the voltage rise by optimally locating and sizing the battery energy storage system (BESS) in PVDG integrated distribution network. The improved firefly algorithm is used to perform optimal placement and sizing. Three objective functions are presented considering the voltage deviation and BESS off-time with state of charge as the constraint. The performance of the proposed method is compared with another optimization method such as the original firefly algorithm and gravitational search algorithm. Simulation results show that the proposed optimum BESS location and size improve the voltage stability.

Keywords: BESS, firefly algorithm, PVDG, voltage fluctuation

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Authors: Abdelaziz Fellah, Allaoua Maamir

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We propose a domain-independent merging-cluster filter approach complemented with a set of algorithms for identifying approximate duplicate entities efficiently and accurately within a single and across multiple data sources. The near-optimal merging-cluster filter (MCF) approach is based on the Monge-Elkan well-tuned algorithm and extended with an affine variant of the Smith-Waterman similarity measure. Then we present constant, variable, and function threshold algorithms that work conceptually in a divide-merge filtering fashion for detecting near duplicates as hierarchical clusters along with their corresponding representatives. The algorithms take recursive refinement approaches in the spirit of filtering, merging, and updating, cluster representatives to detect approximate duplicates at each level of the cluster tree. Experiments show a high effectiveness and accuracy of the MCF approach in detecting approximate duplicates by outperforming the seminal Monge-Elkan’s algorithm on several real-world benchmarks and generated datasets.

Keywords: data mining, data cleaning, approximate duplicates, near-duplicates detection, data mining applications and discovery

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Authors: Mirco Tarozzi, Giacomo Pignagnoli, Andrea Benedetti

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Structural systems are often subjected to degradation processes due to different kind of phenomena like unexpected loadings, ageing of the materials and fatigue cycles. This is true especially for bridges, in which their safety evaluation is crucial for the purpose of a design of planning maintenance. This paper discusses the experimental evaluation of the stiffness reduction from frequency changes due to uniform damage scenario. For this purpose, a 1:4 scaled bridge has been built in the laboratory of the University of Bologna. It is made of concrete and its cross section is composed by a slab linked to four beams. This concrete deck is 6 m long and 3 m wide, and its natural frequencies have been identified dynamically by exciting it with an impact hammer, a dropping weight, or by walking on it randomly. After that, a set of loading cycles has been applied to this bridge in order to produce a uniformly distributed crack pattern. During the loading phase, either cracking moment and yielding moment has been reached. In order to define the relationship between frequency variation and loss in stiffness, the identification of the natural frequencies of the bridge has been performed, before and after the occurrence of the damage, corresponding to each load step. The behavior of breathing cracks and its effect on the natural frequencies has been taken into account in the analytical calculations. By using a sort of exponential function given from the study of lot of experimental tests in the literature, it has been possible to predict the stiffness reduction through the frequency variation measurements. During the load test also crack opening and middle span vertical displacement has been monitored.

Keywords: concrete bridge, damage detection, dynamic test, frequency shifts, operational modal analysis

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Authors: Ram Mohan, Mahendran Samykano, Shyam Aravamudhan

Abstract:

Metallic nanowires with sub-micron and hundreds of nanometer diameter have a diversity of applications in nano/micro-electromechanical systems (NEMS/MEMS). Characterizing the mechanical properties of such sub-micron and nano-scale metallic nanowires are tedious; require sophisticated and careful experimentation to be performed within high-powered microscopy systems (scanning electron microscope (SEM), atomic force microscope (AFM)). Also, needed are nanoscale devices for placing the nanowires; loading them with the intended conditions; obtaining the data for load–deflection during the deformation within the high-powered microscopy environment poses significant challenges. Even picking the grown nanowires and placing them correctly within a nanoscale loading device is not an easy task. Mechanical characterizations through experimental methods for such nanowires are still very limited. Various techniques at different levels of fidelity, resolution, and induced errors have been attempted by material science and nanomaterial researchers. The methods for determining the load, deflection within the nanoscale devices also pose a significant problem. The state of the art is thus still at its infancy. All these factors result and is seen in the wide differences in the characterization curves and the reported properties in the current literature. In this paper, we discuss and present our experimental method, results, and discussions of uniaxial tensile loading and the development of subsequent stress–strain characteristics curves for Nickel nanowires. Nickel nanowires in the diameter range of 220–270 nm were obtained in our laboratory via an electrodeposition method, which is a solution based, template method followed in our present work for growing 1-D Nickel nanowires. Process variables such as the presence of magnetic field, its intensity; and varying electrical current density during the electrodeposition process were found to influence the morphological and physical characteristics including crystal orientation, size of the grown nanowires1. To further understand the correlation and influence of electrodeposition process variables, associated formed structural features of our grown Nickel nanowires to their mechanical properties, careful experiments within scanning electron microscope (SEM) were conducted. Details of the uniaxial tensile characterization, testing methodology, nanoscale testing device, load–deflection characteristics, microscopy images of failure progression, and the subsequent stress–strain curves are discussed and presented.

Keywords: uniaxial tensile characterization, nanowires, electrodeposition, stress-strain, nickel

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Authors: Farzaneh Sarbandi Farahani

Abstract:

Drought and decrease in the level of lakes in recent years due to global warming and excessive use of water resources feeding lakes are of great importance, and this research has provided a structure to investigate this issue. First, the information required for simulating lake drought is provided with strong references and necessary assumptions. Entity-Component-System (ECS) structure has been used for simulation, which can consider assumptions flexibly in simulation. Three major users (i.e., Industry, agriculture, and Domestic users) consume water from groundwater and surface water (i.e., streams, rivers and lakes). Lake Mead has been considered for simulation, and the information necessary to investigate its drought has also been provided. The results are presented in the form of a scenario-based design and optimal strategy selection. For optimal strategy selection, a deep reinforcement algorithm is developed to select the best set of strategies among all possible projects. These results can provide a better view of how to plan to prevent lake drought.

Keywords: drought simulation, Mead lake, entity component system programming, deep reinforcement learning

Procedia PDF Downloads 92

Authors: Amir Hajian, Sepehr Damavandinejadmonfared

Abstract:

In this paper the issue of dimensionality reduction is investigated in finger vein recognition systems using kernel Principal Component Analysis (KPCA). One aspect of KPCA is to find the most appropriate kernel function on finger vein recognition as there are several kernel functions which can be used within PCA-based algorithms. In this paper, however, another side of PCA-based algorithms -particularly KPCA- is investigated. The aspect of dimension of feature vector in PCA-based algorithms is of importance especially when it comes to the real-world applications and usage of such algorithms. It means that a fixed dimension of feature vector has to be set to reduce the dimension of the input and output data and extract the features from them. Then a classifier is performed to classify the data and make the final decision. We analyze KPCA (Polynomial, Gaussian, and Laplacian) in details in this paper and investigate the optimal feature extraction dimension in finger vein recognition using KPCA.

Keywords: biometrics, finger vein recognition, principal component analysis (PCA), kernel principal component analysis (KPCA)

Procedia PDF Downloads 365

Authors: Abdorreza Rabiee, Shahla Mohammad Hoseini Mirzaei

Abstract:

The advantages of distributed generations (DGs) based on renewable energy sources (RESs) leads to high penetration level of DGs in distribution network. With incorporation of DGs in distribution systems, the system reliability and security, as well as voltage profile, is improved. However, the protection of such systems is still challenging. In this paper, at first, the related papers are reviewed and then a practical scheme is proposed for coordination of OCRs in distribution system with DGs. The coordination problem is formulated as a nonlinear programming (NLP) optimization problem with the object function of minimizing total operating time of OCRs. The proposed method is studied based on a simple test system. The optimization problem is solved by General Algebraic Modeling System (GAMS) to calculate the optimal time dial setting (TDS) and also pickup current setting of OCRs. The results show the effectiveness of the proposed method and its applicability.

Keywords: distributed generation, DG, distribution network, over current relay, OCR, protection coordination, pickup current, time dial setting, TDS

Procedia PDF Downloads 139

Authors: Golnar Behzadi, Michael O'Sullivan, Tava Olsen, Abraham Zhang

Abstract:

By definition, increasing supply chain resilience improves the supply chain’s ability to return to normal, or to an even more desirable situation, quickly and efficiently after being hit by a disruption. This is especially critical in agribusiness supply chains where the products are perishable and have a short life-cycle. In this paper, we propose a resilience metric to capture and improve the recovery process in terms of both performance and time, of an agribusiness supply chain following either supply or demand-side disruption. We build a model that determines optimal supply chain recovery planning decisions and selects the best resilient strategies that minimize the loss of profit during the recovery time window. The model is formulated as a two-stage stochastic mixed-integer linear programming problem and solved with a branch-and-cut algorithm. The results show that the optimal recovery schedule is highly dependent on the duration of the time-window allowed for recovery. In addition, the profit loss during recovery is reduced by utilizing the proposed resilient actions.

Keywords: agribusiness supply chain, recovery, resilience metric, risk management

Procedia PDF Downloads 397